Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states 'pretty-print' which implies a non-destructive formatting operation, but does not disclose whether it validates JSON, what happens on invalid input, or any other behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (two sentences) and front-loaded with the core purpose. It wastes no words, though it could add a bit more detail without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple tool and absence of output schema, the description should at least specify the output format (e.g., a formatted JSON string) and confirm it is read-only. It does not provide this, and with many JSON sibling tools, it lacks distinguishing guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% with no parameter descriptions. The description mentions 'with indent' but does not explain that 'text' should be a JSON string or the unit/range of 'indent'. This forces the agent to infer parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the action 'pretty-print JSON' and the resource 'JSON'. It also provides a use case 'when the agent needs readable output', which distinguishes it from other JSON tools like validation or conversion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a 'When' clause ('when the agent needs readable output'), offering some usage context. However, it does not explicitly exclude use cases or compare with alternatives (e.g., json_minify, json_validate), leaving room for ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.